Podem escriure text descriptiu. Així podem donar tot tipus d'explicacions perquè el lector sàpiga què estem fent.
També podem incloure codi, com veurem a continuació.
Comencem amb alguns exemples.
def print_hi(name):
print(f'Hi, {name}')
if __name__ == '__main__':
print_hi('PyCharm')
Hi, PyCharm
Un altre exemple:
cars = ['Volvo', 'Seat', 'VW', 'Mercedes']
print (cars[1])
Seat
I ara fem un dibuix
import pandas as pd
import plotly.express as px
# Create pandas DataFrame from a CSV and concatenate a second DataFrame
df = pd.read_csv('C:/Users/Pep/Documents/Figura2.csv')
df1 = pd.read_csv('C:/Users/Pep/Documents/Figura3.csv')
df = pd.concat([df, df1], ignore_index=True)
# Make legend discrete
df['Series'] = df['Series'].astype(str)
print(df)
# Plot the data
fig = px.scatter(df, x='Date', y='Antimony', color='Series',
title='Test scatter plot',
labels=dict(Date='Year of publication',
Antimony='Antimony / ng L<sup>-1</sup>', Series='Series number')
)
fig.update_traces(marker=dict(size=12,
line=dict(width=0)),
selector=dict(mode='markers'))
fig.update_yaxes(range=[0, 1000],
minor_ticks="inside", tickcolor='black',
ticks="inside", ticklen=8, minor_ticklen=5,
showline=True, linewidth=1, linecolor='black', mirror=True,
showgrid=True, gridwidth=1, gridcolor='grey')
fig.update_xaxes(showline=True, linewidth=1, linecolor='black', mirror=True,
showgrid=True, gridwidth=1, gridcolor='grey',
minor_ticks="inside", minor_ticklen=5, minor_dtick=1) # nticks=15
# Create plot
fig.show()
Date Antimony Series 0 1965 260.0 1 1 1965 460.0 1 2 1965 240.0 1 3 1965 210.0 1 4 1965 250.0 1 .. ... ... ... 123 2013 368.0 4 124 2013 525.0 4 125 2013 259.0 4 126 2016 164.0 4 127 2020 438.0 4 [128 rows x 3 columns]